JP3520166B2 - Image processing device - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing device having a wavelet transform function.

[0002]

2. Description of the Related Art Conventionally, an image forming apparatus is generally required to have high-speed processing and high definition of image data. For example,
Japanese Patent Laid-Open No. 7-79346, "Image Coding Method and Apparatus", determines whether or not the data quantized by the orthogonal transform unit is invalid for each stage, and deletes the information accordingly.
The amount of data to be transmitted is reduced and the time required for the encoding process is shortened.

[0003]

However, in the above-mentioned conventional example, although the data amount is reduced, the image quality is not guaranteed. Further, a dither method, an error diffusion method, or the like is used when binarizing a multivalued image, but this requires a lot of processing time because all pixels are compared. Similarly, when performing gamma conversion on an image, a large amount of processing time is required because all pixels are processed. Further, there is nothing satisfying at the same time that the user can select either processing speed or high image quality.

It is an object of the present invention to provide an image processing device having a wavelet transform function that enables diversification and speeding up of binarization processing.

[0005]

In order to achieve the above object, the image processing apparatus according to the first aspect of the invention has an image data processing apparatus.
Input means for inputting data, wavelet transform means for wavelet transforming bit map data based on this image data, and wavelet transform means
The compression means for compressing the conversion coefficient , the expansion means for expanding the conversion coefficient compressed by the compression means, and the expansion means
In the image processing apparatus configured with a binarizing unit that binarizes the expanded transform coefficient , the wavelet transform is performed.
Of the transform coefficients generated by the method , only the low frequency components are expanded.
It is characterized in that it is expanded by the long means and binarized by the binarizing means .

[0006] Further, the extension which is extended by the extension means is
A way to inverse wavelet transform coefficients as needed
It is characterized by having a Bullet inverse transformation means. It
In addition, it is preferable to perform gamma conversion only on the low-frequency components generated by the above wavelet transform so that processing can be performed faster than normal gamma conversion.

An image processing apparatus according to a fourth aspect of the invention is
Input means for inputting image data and a base for this image data
The brute bitmap data and wavelet transformation means for wavelet transform, the wavelet transform unit
A compression means for compressing the obtained transform coefficient , and this compression
And decompressing means for decompressing the transform coefficients compressed by means,
Webure the transform coefficients decompressed by the decompressing means
A wavelet inverse transform means for Tsu preparative reverse transformation, the web
Image data restored by the doublet inverse transform means 2
In an image processing apparatus having a binarizing means for binarizing, in the mode in which speed is prioritized, the wavelet
Of the low-frequency component of the conversion coefficient generated by the
Only the decompressing means and the binarizing means for binarizing
However, in modes that give priority to image quality, the wavelet transform
All the components of the conversion coefficient generated by the conversion means are expanded by the expansion means.
It is characterized in that it is expanded and binarized by the binarizing means .

The image processing apparatus according to the invention of claim 5 is
Input means for inputting image data and a base for this image data
Wavelet transform of the following bitmap data
Wavelet transform means and this wavelet transform means
A compression means for compressing the obtained transform coefficient, and this compression
Decompression means for decompressing the transform coefficient compressed by the means,
The transform coefficient expanded by this expansion means
Wavelet inverse transform means for
Image data restored by the doublet inverse transform means
The image processing device configured and a binarizing means for reduction, transform coefficient generated by the wavelet transform
Depending on the size relationship between the compressed size of the number and a predetermined threshold
Process the transform coefficients generated by the wavelet transform means.
It is characterized by switching the processing mode . Then, the upper Symbol processing mode, the wavelet transform unit
A speed-first model that processes the low-frequency components of the generated transform coefficients.
Of the transform coefficients generated by the code or wavelet transform means
This is an image quality priority mode in which all components are processed .

[0009]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Next, an embodiment of an image processing apparatus according to the present invention will be described in detail with reference to the accompanying drawings. Figure 1
~ Referring to Fig. 5, there is shown one embodiment of the image processing apparatus of the present invention.

FIG. 1 is a block diagram showing an example of the overall configuration of an embodiment of an image processing apparatus of the present invention. In FIG.
The image processing apparatus of this embodiment includes a host 1, a FIP unit 2,
It is composed of a frame memory 3, an HDD 4, a compression / expansion unit 5, a wavelet conversion unit 6, a binarization processing unit 7, and an engine 8.

In the image processing apparatus configured as described above,
The page description data sent from the host 1 is the RIP unit 2
It is converted into bitmap data by and is stored in the frame memory 3 which is the first storage unit. When the bitmap data for one page is completed here, this data is transferred to the wavelet transform processing unit 6. The data (coefficients) converted by the wavelet conversion unit 6 are compressed /
It is transferred to the decompression unit 5. There is a small-capacity buffer memory in the compression / expansion section, which can be used for QM-Code
Data compression such as r is performed. The compressed data is stored in the hard disk drive (HDD) 4 that is the second storage unit.
Are sequentially written to. The written data is read when an output request is received, expanded by the compression / expansion unit 5, and inversely converted again by the wavelet conversion unit 6 when necessary,
The binarization processing unit 7 performs binarization processing, and then outputs through the engine 8.

FIG. 2 is a process flow chart showing the first operation example of this embodiment. In FIG. 2, the input image (201) converted into bitmap data is converted into four levels from a high frequency component to a low frequency component by the wavelet transform unit 6 (202). As a result, L for each level
Four components of L, LH, HL, HH are made. The compression / expansion unit 5 performs data compression on each component (203) and once saves it in the storage means of the HDD 4 (204). Next, only the previously compressed LL component is expanded (205). The density pattern method is applied to this to restore the LL layers (20
6). For example, if LL is one layer (1/4 pixel), LL
Is converted by a 2 × 2 pattern to create and output binary bitmap data (207).

FIG. 3 is a process flow chart showing a second operation example of the present embodiment. In FIG. 3, first, the user selects the output mode as speed priority or image quality priority (301). The input image (302) converted into bitmap data is converted into four levels from high frequency components to low frequency components by the wavelet transform unit 6 (303). As a result, four components of LL, LH, HL, and HH are created for each level. Data compression is performed for each component (30
4) Once stored in the storage means of the HDD 4 (305).
Next, when the user has selected the speed priority mode, only the LL component generated by the wavelet transform unit 6 is expanded (306), the density pattern method is applied to it, and the binarization processing unit 7 binarizes it. (307). If the user has selected the image quality priority mode, all the components generated by the wavelet transform unit 6 are expanded (308), inverse wavelet transform is performed on these components to restore the image (309), and the dither method The data is digitized (310), bitmap data is created and output (311).

FIG. 4 is a process flow chart showing a third operation example of this embodiment. In FIG. 4, the input image (401) converted into bitmap data is converted by the wavelet conversion unit 6 into four levels from high frequency components to low frequency components (402). As a result, L for each level
Four components of L, LH, HL, HH are made. Data is compressed for each component (403) and once stored in the storage means of the HDD 4 (404). Next, if the compression size performed previously is greater than a certain value (405), it is determined that the image restoration processing is not in time for drawing, and only the LL component is expanded by giving priority to the speed (406), and the density pattern method is applied. Give 2
The value is converted (407). If it is less than a certain value (40
5) Prioritize image quality, decompress all four components generated by the wavelet transform unit 6 (408), inverse wavelet transform these to restore the image (409), and binarize by dither method (410), Bit map data is created and output (411).

FIG. 5 is a process flowchart showing a fourth operation example of this embodiment. In FIG. 5, the input image (501) converted into bitmap data is converted into four levels from a high frequency component to a low frequency component by the wavelet transform unit 6 (502). As a result, L for each level
Four components of L, LH, HL, HH are made. Data is compressed for each component (503) and once stored in the storage means of the HDD 4 (504). Next, LL which is a low frequency component
Only the coefficient of is expanded (505). This is subjected to gamma conversion (506) and further subjected to the density pattern method to restore the LL layers (507). For example, LL has one layer (1
/ 4 pixels), LL is converted in a 2 × 2 pattern,
Create and output binary bitmap data (50
8).

[0016]

As is apparent from the above description, claim 1
The image processing apparatus according to the invention described in (3) expands only the low-frequency component of the wavelet coefficient generated by the wavelet transform, and binarizes it at high speed by the density pattern method according to the output resolution and prints it. Therefore, it is possible to perform binarization processing at high speed by converting the input image data into wavelet transform coefficients and using only the low frequency component of the wavelet transform coefficients.

Further, gamma conversion is applied only to the low frequency components generated by the above wavelet transform. Therefore, when performing gamma conversion, the input image data is converted into wavelet transform coefficients, and only the low-frequency component of them is subjected to gamma conversion, which is then used to perform high-speed gamma conversion on software, and to perform binary conversion. It is possible to create a converted image.

An image processing apparatus according to a fourth aspect of the invention is
Prepare a method to perform data compression / expansion using all components of wavelet coefficients, perform inverse wavelet transform and perform binarization processing on the restored image. If you want to prioritize speed, process with wavelet transform to improve image quality. When it is desired to give priority, the processing is performed by binarization, and the processing method can be switched depending on which of image quality and speed is prioritized. Therefore, 2
It is possible to prepare two types of binarization methods, and the user can select the processing method that he prefers in terms of image quality and speed. As a result, a complicated document can be compressed and normally printed without adding memory. Also, depending on the user's selection, either speed or image quality can be prioritized for processing depending on how the coefficient is used.

An image processing apparatus according to a fifth aspect of the invention is
If the compressed size of the coefficients generated by the wavelet transform exceeds a specified size, the process is performed in the speed priority mode that uses only low frequency components, and if not, all components are used. The process is automatically performed by switching between these processing modes. Therefore, when there is a possibility that normal printing cannot be performed, the mode is automatically switched to a mode in which speed is prioritized, and normal printing can always be performed with a small amount of memory. By automatically changing the processing method depending on the compressed data size, it is possible to avoid outputting an image for which drawing failed.

[Brief description of drawings]

FIG. 1 is a block diagram showing an example of the overall configuration of an embodiment of an image processing apparatus of the present invention.

FIG. 2 is a processing flowchart showing a first operation example.

FIG. 3 is a processing flowchart showing a second operation example.

FIG. 4 is a processing flowchart showing a third operation example.

FIG. 5 is a processing flowchart showing a fourth operation example.

[Explanation of symbols]

1 host 2 FIP section 3 frame memory 4 HDD 5 compression / expansion section 6 Wavelet transform unit 7 Binarization processing unit 8 engine

Claims (5)

(57) [Claims] 1. Input means for inputting image data, wavelet transform means for wavelet transforming bitmap data based on said image data, compression means for compressing transform coefficients obtained by said wavelet transform means, and compressed A storage unit for storing the conversion coefficient, a decompression unit for reading the compressed conversion coefficient from the storage unit in response to an output request and decompressing it, and a binarization unit for binarizing the conversion coefficient decompressed by the decompression unit. Among the transform coefficients generated by the wavelet transforming means, only the low frequency component is expanded by the expanding means, the density pattern method is applied, and binarized by the binarizing means. Image processing device. 2. The image processing apparatus according to claim 1, further comprising wavelet inverse transforming means for subjecting the transform coefficient decompressed by the decompressing means to wavelet inverse transforming as required. 3. The image processing apparatus according to claim 1, wherein the gamma conversion processing is performed only on the conversion coefficient of the low frequency component generated by the wavelet conversion means. 4. Input means for inputting image data, wavelet transform means for wavelet transforming bitmap data based on the image data, compression means for compressing transform coefficients obtained by the wavelet transform means, and compressed Storage means for storing the transform coefficient, decompression means for reading the compressed transform coefficient from the storage means in response to an output request and decompressing it, and wavelet inverse transform means for inversely transforming the transform coefficient decompressed by the decompressing means by wavelet inverse transform. And a binarizing means for binarizing the image data restored by the wavelet inverse transforming means. In the mode giving priority to speed, only the low frequency component of the transform coefficients generated by the wavelet transforming means Is expanded by the expanding means, subjected to a density pattern method, and binarized by the binarizing means. In the image quality priority mode, all the components of the transform coefficient generated by the wavelet transforming unit are expanded by the expanding unit, dithered, and binarized by the binarizing unit. Processing equipment. 5. Input means for inputting image data, wavelet transform means for wavelet transforming bitmap data based on said image data, compression means for compressing transform coefficients obtained by said wavelet transform means, and compressed Storage means for storing the transform coefficient, decompression means for reading the compressed transform coefficient from the storage means in response to an output request and decompressing it, and wavelet inverse transform means for inversely transforming the transform coefficient decompressed by the decompressing means by wavelet inverse transform. And binarizing means for binarizing the image data restored by the wavelet inverse transforming means. When the compressed size of the transform coefficient generated by the wavelet transform is larger than a predetermined value, the wave
Low-frequency component of the transform coefficient generated by the doublet transform means
Is expanded and subjected to a density pattern method to be binarized,
Is less than the predetermined value, the wavelet transform is
All the components of the transform coefficient generated by the conversion means are expanded and dithered.
An image processing apparatus, which performs binarization by applying a method .